The present invention relates to the field of signal measurement. More specifically, the present invention relates to the field of integral and simultaneous signal measurement and measurement device calibration.
For accurate instrumentation, it is desirable to fully understand the characteristics of the devices used. With any given one of these devices, i.e., a xe2x80x9cdevice-under-testxe2x80x9d or DUT, the specific characteristics of that DUT are not fully understood. As a simplistic example, a given xe2x80x9c47 kxcexa9xe2x80x9d resistor would rarely have a value of exactly 47,000xcexa9. To properly understand the operation of a circuit containing such a resistor, a knowledge of the actual resistance (e.g., 46,985.42xcexa9) would be helpful. It should be understood that a DUT may encompass a wide range of electrical components, equipment, and systems. A typical DUT may be a filter, an amplifier, a transmitter, a receiver, or any component, group of components, circuit, module, device, system, etc.
The drift of components, filters, amplifiers, and other signal-conditioning circuitry typically limits the accuracy of electronic measurements. A measurement system may advertise a large dynamic range and very-high resolution. However, the full dynamic range and resolution may not be realizable because of errors inherent in the system. Current measurement systems have not been demonstrated to have verifiable, full-scale uncertainties of better than 0.1 percent over all types of errors.
Real-world measurement instruments tend not to be perfect. This imperfection will affect the accuracy of the resulting measurements. This accuracy is dependent upon measurement errors. Such errors may be classed as static (systematic) errors and dynamic errors.
Static errors are repeatable, time-invariant system errors. That is, static errors do not vary over time. Static errors result from the nonideal aspects of a system. These errors are repeatable as long as no changes are made to the system. Static errors include directivity errors, source-mismatch errors, load-mismatch errors, reflection and transmission tracking errors, isolation or cross-talk errors, etc.
Static errors may be reduced through the use of precision components and circuits. However, no matter how precisely a circuit is designed, there will still be some level of static error present. Since static errors are repeatable, they can be suppressed using various static error suppression techniques, such as twelve-term error modeling, known to those skilled in the art. Twelve-term error modeling, typically employed with standard network analyzers, can account for directivity errors, source-mismatch errors, load-mismatch errors, tracking errors, and isolation errors.
Before error modeling may be employed, the error coefficients of the requisite equations must be calculated by making a set of measurements on a set of known loads meeting precise standards. A sufficient number of precise standards must be used in order to determine the various error coefficients in the error model. A common static-error calibration technique is the Short, Open, Load, and Through (SOLT) technique. The SOLT calibration technique yields better than 0.1 percent accuracy for static errors. However, dynamic errors limit the actual accuracy to less than this. An alternative static-error calibration technique, also well-known to those skilled in the art, is the Through, Reflection, and Load (TRL) technique. The TRL calibration technique yields significantly better static-error accuracy than the SOLT technique at the cost of calibration complexity. There are a number of other well-known static-error calibration techniques that may be used to advantage in specific instances.
However, removing a significant amount of static error achieves little if other types of errors are not also addressed. Dynamic errors are time-varying errors. That is, dynamic errors change over time, often in an unpredictable manner. Such errors may be attributable to a number of different sources. For example, component-drift, physical-device (e.g., cables, connectors, etc.) errors, phase-noise errors, random noise, etc.
Measurement systems exhibit several types of dynamic errors. Phase-noise errors and random errors, while inherently dynamic (i.e., time-variant) are special cases independently discussed hereinafter.
Component-drift errors may be either long-term or short-term. Long-term component-drift errors, however, are typically due to aging of the components, with resultant variations in component specifications.
One type of short-term component-drift error, source drift error, is usually attributable to thermal or mechanical variations within the system, and may include both amplitude and phase fluctuations of the output wave.
Another type of short-term component-drift error, receiver drift error, is associated with a data receiver. This may be due to drift in components such as amplifiers, filters, and analog-to-digital converters. Receiver-drift error may also appear as time-varying gain and phase drift in the received signals.
Thermal variations may also lead to physical expansion of passive components within the system. At high frequencies, such expansion may lead to appreciable phase errors. In applications where the DUT is located at a considerable distance from a transmitter and/or receiver, there may be a number of time-varying errors associated with the connections between the DUT and the transmitter and receiver. These may include amplitude and phase-drift errors in the amplifiers or errors associated with the modulation and demodulation circuitry. Systems in which such errors become significant include systems utilizing propagation media other than traditional cables (e.g., the atmosphere, space, the earth, railroad tracks, power transmission lines, the oceans, etc.).
Dynamic physical errors result from physical changes in the test setup. One example of a physical error is connector repeatability. As one connects and disconnects the DUT, there will be reflection and transmission errors associated with any nonrepeatability of the connectors. The severity of the connector repeatability error is related to the type of connector, the condition of the connector, and the care with which the user makes the connection.
Another type of dynamic physical errors are cable-flexure errors. Cable-flexure errors appear as one moves the cables to connect or disconnect a DUT or perform a calibration. Time-variant phase errors associated with the relaxation of the cable can occur for a period of time after the cable has been flexed.
Phase noise (jitter) is directly related to the frequency stability of a signal source. In a perfect sinusoidal oscillator, all the energy would lie at a single frequency. Since oscillators are not perfect, however, the energy will be spread slightly in frequency. This results in a pedestal effect. This effect, referred to as phase noise, is more severe at higher frequencies. Phase noise is a performance-limiting factor in applications where a weak signal must be detected in the presence of a stronger, interfering signal.
Random or white noise is common in measurement systems. Random noise includes thermal noise, shot noise, and electromagnetic interference. Random noise may appear as random data errors. Traditional and well-known techniques of random error suppression utilize some form of oversampling to determine the correct data and suppress the random errors.
Calibration frequency is also a problem in conventional signal measurement systems. Typically, high-accuracy measurement systems employing manual calibration are calibrated periodically. The interval between calibrations may be hourly, daily, weekly, monthly, quarterly, or even yearly. This technique produces a steadily decreasing accuracy that progresses over the inter-calibration interval. Additionally, drift errors occurring during the inter-calibration interval are uncompensated. Such drift errors tend to accumulate. Therefore, measurements taken shortly before calibration may be suspect. Exactly how suspect such measurements may be depends upon the length of the inter-calibration interval and the amount of drift involved.
Many state-of-the-art measurement systems employ automatic-calibration techniques. Some automatic-calibration systems calibrate at specified intervals. Such systems suffer the same decreasing accuracy as manual-calibration systems.
Other automatic-calibration systems calibrate at the beginning and end of each measurement cycle. The use of frequent nonsimultaneous calibration procedures does increase overall accuracy, but may also greatly increase the cost of measurements and prevents measurements while the frequent calibration procedures are taking place.
All calibration procedures discussed above are nonsimultaneous. That is, the calibration procedures do not occur simultaneously with measurement. Nonsimultaneous calibration procedures are incapable of correcting or compensating for dynamic errors, such as component drift, occurring during measurement..
Current technology demands increasingly small operational errors. High accuracy is therefore a growing need of instrumentation users. Measurement systems utilizing simultaneous calibration are useful for applications requiring high-accuracy measurements. That is, systems are needed that calibrate themselves and measure data simultaneously. Such systems are said to employ dynamic error suppression. That is, such systems are able to compensate for dynamic (time-variant) errors by continuously calibrating themselves while simultaneously performing the requisite measurements.
As current technology drives operational frequencies higher and higher, phase noise (i.e., signal jitter) increases in importance. A definite need exists, therefore, for systems employing phase-noise error suppression. That is, for systems employing some means of compensating for signal jitter. This is especially important in polyphase-constellation communications systems where phase noise may cause misinterpretation of the signal phase point (i.e., the data) at any given instant.
Measurement systems for state-of-the-art technology also desirably compensate for random errors.
Accordingly, it is an advantage of the present invention that a real-time error-suppression technique is provided.
It is another advantage of the present invention that an apparatus for real-time error-suppression is provided.
It is another advantage of the present invention that a technique is provided to effect thorough error suppression, i.e., static error suppression, dynamic error suppression, phase-noise error suppression, and random error suppression.
It is another advantage of the present invention that simultaneous calibration is provided to allow dynamic error suppression.
It is another advantage of the present invention that signal normalization is provided to effect thorough error suppression.
It is another advantage of the present invention that simultaneous measurement of both data and normalization signals is provided to allow thorough error suppression.
It is another advantage of the present invention that a phase-noise reference signal is provided to effect phase noise suppression.
It is another advantage of the present invention that frequency offsetting is provided to effect discrete signal normalization.
It is another advantage of the present invention that the normalization signals are created from the data signal.
It is another advantage of the present invention that a bidirectional link is provided between input and output transmission signals to effect system calibration.
The above and other advantages of the present invention are carried out in one form by a signal measurement method incorporating real-time error suppression, which method includes combining a first signal and a second signal offset in frequency from the first signal to produce a third signal, propagating the third signal over a signal path capable of inducing errors to produce a fourth signal, separating the fourth signal into a fifth signal and a sixth signal, comparing the sixth signal against the second signal to determine a correction factor, and applying the correction factor to the fifth signal to extract a replica of the first signal therefrom.
The above and other advantages of the present invention are carried out in another form by a signal measurement system incorporating real-time error suppression, which system incorporates a signal source generating a first signal, a first mixer offsetting the first signal to produce a second signal, a second mixer offsetting the first signal to produce a third signal, a combiner combining the second and third signals to produce a fourth signal, a propagation medium propagating the fourth signal over a potentially corruptive signal path to produce an analog fifth signal, an analog-to-digital converter converting the analog fifth signal into a digital sixth signal, and a processor containing a separation routine separating the sixth signal into seventh and eighth signals, a comparison routine comparing the eighth signal against the third signal to determine a correction factor, and a correction routine applying the correction factor to the seventh signal to extract a replica of the second signal therefrom.
The above and other advantages of the present invention are carried out in another form by a signal measurement method for a device-under-test having a first port and a second port, which method incorporates coupling a first probe to the first port, coupling a second probe to the second port, producing a first signal, extracting a second signal from the first signal, propagating the second signal into the first port, deriving a third signal from the second signal within the device-under-test, propagating the third signal from the second port, deriving a fourth signal from the second signal, deriving a fifth signal from the first signal, deriving a sixth signal from the third signal, deriving a seventh signal from the first signal, reciprocally propagating the fifth and seventh signals from the first and second probes to the second and first probes, respectively, over a common signal path, combining the fourth and seventh signals to produce an eighth signal, and combining the sixth and fifth signals to produce a ninth signal.
The above and other advantages of the present invention are carried out in another form by a signal measurement system incorporating a device-under-test having a first port and a second port, a first probe coupled to the first port, a second probe coupled to the second port, a signal source generating a first signal, an input circuit extracting a second signal from the first signal and propagating the second signal into the first port, an output circuit deriving a third signal from the second signal and propagating the third signal from the second port, a first mixer producing a fourth signal from the second signal, a second mixer producing a fifth signal from the first signal, a third mixer producing a sixth signal from the third signal, a fourth mixer producing a seventh signal from the first signal, a trans-probe propagation medium reciprocally propagating the fifth and seventh signals from the first and second probes to the second and first probes, respectively, over a common signal path, a first combiner combining the fourth and seventh signals into an eighth signal, and a second combiner combining the sixth and fifth signals into a ninth signal.